Projects per year
Abstract
With speech annotation being one of the most time-consuming and costly aspects of speech corpora development,there is a significant interest in the development of automatic annotation tools. The present study focuses on variant-independent prosodic boundary annotations for German. We test a previously proposed unsupervised approach, which posits prosodic boundaries based only on acoustic cues. The experiments were conducted on read speech from two corpora, one of Standard German, the Kiel Corpus of Spoken German, and the other of Austrian German, the Graz Corpus of Read and Spontaneous Speech. Averaging across all speakers in the dataset,the tool attained an area under the precision-recall curve of0.308 and 0.215, for the Kiel corpus and the GRASS corpus,respectively. The significant differences obtained in detection across the two varieties were accompanied by large differences between speakers, as well. This was confirmed by a subsequent analysis of the acoustic cues employed in the process, which showed important differences in the way speakers make use of those cues for marking prosodic structure. We discuss these findings with respect to the current literature and their implication for variant-independent automatic annotation.
Original language | English |
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Title of host publication | Proceedings of Speech Prosody 2020 |
Subtitle of host publication | 10th International Conference on Speech Prosody 2020 |
Place of Publication | Tokyo, Japan |
Pages | 990- 994 |
Number of pages | 5 |
Volume | 2020-May |
DOIs | |
Publication status | Published - 1 Jan 2020 |
Publication series
Name | Proceedings of the International Conference on Speech Prosody |
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ISSN (Print) | 2333-2042 |
Keywords
- Acoustic features
- Austrian German
- Automatic detection
- Prosodic phrase boundaries
ASJC Scopus subject areas
- Language and Linguistics
- Linguistics and Language
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Dive into the research topics of 'An analysis of prosodic boundary detection in German and Austrian German read speech'. Together they form a unique fingerprint.Projects
- 1 Finished
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FWF - CLCS_2 - Cross-layer prosodic models for conversational speech
1/10/18 → 30/11/21
Project: Research project
Prizes
Press/Media
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Wie der Mensch von der Maschine lernt
Barbara Schuppler & Gernot Kubin
25/09/19
1 Media contribution
Press/Media: Press / Media